Put.io MCP Server

Overview

The Put.io MCP server bridges the gap between AI assistants and the Put.io cloud‑storage service, enabling seamless management of file transfers directly from an AI workflow. By exposing Put.io’s REST API through the Model Context Protocol, developers can let Claude or other MCP‑compatible assistants orchestrate downloads, cancellations, and link retrieval without leaving the conversational interface. This integration removes the need for manual API calls or third‑party tools, turning file transfer management into a natural part of an AI‑driven task flow.

What Problem It Solves

Managing remote downloads can be tedious, especially when juggling multiple sources or automating content ingestion. Traditional approaches require separate CLI tools or web dashboards, each with its own authentication flow. The Put.io MCP server eliminates this friction by providing a single, authenticated endpoint that an AI assistant can call to start, monitor, or cancel transfers. Developers who rely on automated content pipelines—such as media curators, data scientists ingesting large datasets, or researchers downloading research papers—no longer need to write custom scripts; the AI can handle it all on demand.

Core Capabilities

• Transfer Enumeration – List active or pending transfers, giving the assistant visibility into what is currently being processed.
• Transfer Initiation – Add new downloads by supplying a URL or magnet link, enabling the assistant to fetch media or torrent files on behalf of the user.
• Transfer Cancellation – Abort unwanted or stalled transfers, giving immediate control over bandwidth and storage usage.
• Link Retrieval – Generate browser‑ready URLs for completed transfers, allowing the assistant to share or embed download links directly in conversations.

These features are exposed through simple, well‑documented MCP calls that return JSON payloads. The server handles authentication via an environment variable (), keeping sensitive credentials out of the chat history.

Real‑World Use Cases

• Automated Media Aggregation – A media bot can pull the latest episodes from a torrent tracker, upload them to Put.io, and share access links with subscribers.
• Research Data Collection – An AI assistant can fetch datasets from public repositories, store them in Put.io, and notify a data scientist when the download completes.
• Backup Automation – Developers can schedule nightly backups of project artifacts to Put.io, using the MCP server to start and monitor the transfer without manual intervention.

Integration with AI Workflows

Incorporating this server into an MCP‑enabled assistant is straightforward: the client declares a server in its configuration, and the assistant can invoke actions like , , or as part of a conversation. Because the server operates over HTTP, it fits naturally into existing request–response patterns used by AI assistants for tool calls. Developers can compose higher‑level prompts that trigger these actions, chain responses together, and even embed conditional logic based on transfer status—all within the assistant’s dialogue.

Unique Advantages

• Zero‑Code Interaction – No need to write or maintain custom scripts; the MCP server handles API authentication and request formatting.
• Unified Auth Flow – Credentials are stored once in the environment, reducing the risk of accidental exposure.
• Extensibility – The server’s design allows future expansion (e.g., adding folder management or file metadata retrieval) without changing the client’s integration logic.

Overall, the Put.io MCP server turns a specialized cloud‑storage service into an AI‑friendly tool, empowering developers to build richer, more automated workflows that include file transfer management as a first‑class citizen.